docstr: :param x: input layer
  :param ref: reference usually data in
  :return:
docstr_tok: [":","param","x",":","input","layer",":","param","ref",":","reference","usually","data","in",":","return",":"]
code: def forward(self, x, ref):
      """
  
      :param x: input layer
      :param ref: reference usually data in
      :return:
      """
      for axis in range(self.axis, x.dim()):
          ref_size = ref.size(axis)
          indices = torch.arange(
              self.offset, self.offset + ref_size
          ).long()
          indices = (
              x.data.new().resize_(indices.size()).copy_(indices).long()
          )
          x = x.index_select(axis, Variable(indices))
      return x
  
imports: import torch
  import torch.nn.functional
  from torch import nn
  from .None import Resnet
  from .wider_resnet import wider_resnet38_a2
  from .mynn import initialize_weights, Norm2d
  from torch.autograd import Variable
  from .my_functionals import GatedSpatialConv
  import cv2
  import numpy
label_desc: Use image node_id 2 for calling the Crop obj's underlying member method code with example usage: obj.forward(x, ref) and returns: x